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Record W4200536381 · doi:10.9778/cmajo.20210102

Infection control measures to prevent outbreaks of COVID-19 in Quebec hemodialysis units: a cross-sectional survey

2021· article· en· W4200536381 on OpenAlexafffundvenueabout
William Beaubien‐Souligny, Annie‐Claire Nadeau‐Fredette, Marie-Noël Nguyen, Norka Rios, Marie-Line Caron, Alexander Tom, Rita S. Suri

Bibliographic record

VenueCMAJ Open · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcGill UniversityCentre Hospitalier de l’Université de MontréalHôpital Maisonneuve-RosemontMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineCross-sectional studyInfection controlCoronavirus disease 2019 (COVID-19)OutbreakPandemicHemodialysisEmergency medicineMedical emergencyIntensive care medicineInternal medicineDiseaseVirologyPathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Limited space and resources are potential obstacles to infection prevention and control (IPAC) measures in in-centre hemodialysis units. We aimed to assess IPAC measures implemented in Quebec's hemodialysis units during the spring of 2020, describe the characteristics of these units and document the cumulative infection rates during the first year of the COVID-19 pandemic. METHODS: For this cross-sectional survey, we invited leaders from 54 hemodialysis units in Quebec to report information on the physical characteristics of the unit and their perceptions of crowdedness, which IPAC measures were implemented from Mar. 1 to June 30, 2020, and adherence to and feasibility of appropriate IPAC measures. Participating units were contacted again in March 2021 to collect information on the number of COVID-19 cases in order to derive the cumulative infection rate of each unit. RESULTS: Data were obtained from 38 of the 54 units contacted (70% response rate), which provided care to 4485 patients at the time of survey completion. Fourteen units (37%) had implemented appropriate IPAC measures by 3 weeks after Mar. 1, and all 38 units had implemented them by 6 weeks after. One-third of units were perceived as crowded. General measures, masks and screening questionnaires were used in more than 80% of units, and various distancing measures in 55%-71%; reduction in dialysis frequency was rare. Data on cumulative infection rates were obtained from 27 units providing care to 4227 patients. The cumulative infection rate varied from 0% to 50% (median 11.3%, interquartile range 5.2%-20.2%) and was higher than the reported cumulative infection rate in the corresponding region in 23 (85%) of the 27 units. INTERPRETATION: Rates of COVID-19 infection among hemodialysis recipients in Quebec were elevated compared to the general population during the first year of the pandemic, and although hemodialysis units throughout the province implemented appropriate IPAC measures rapidly in the spring of 2020, many units were crowded and could not maintain physical distancing. Future hemodialysis units should be designed to minimize airborne and droplet transmission of infection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.140
GPT teacher head0.442
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes4
Has abstractyes

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